DESCRIPTION(provided by applicant): The identification of valid, robust biomarkers of aging and age-related processes has been an elusive goal. Dietary restriction (DR, long term, low calorie diets) has established efficacy in increasing longevity and decreasing morbidity in rodents. We have now identified 93 components of the sera metabolome that define a DR serotype - i.e., a metabolic serotype or biomarker profile that reflects caloric intake. Megavariate pattern recognition analysis has identified metabolic profiles in both male and female rats that distinguish ad libitum fed and DR rats (100% accuracy in training sets, mean >90% in test sets). Profiles are robust across the lifespan (6,12,18,24, and 30 months). Profiles reflect duration of DR (fasted, 1, 2, 4, 8 weeks) and extent of restriction (10,20,30, 40% DR, r2 = 0.88 for N = 90). Profiles also distinguish long- and short-lived strains of mice, suggesting that at the profile, at least in part, reflects the physiological benefits of DR in addition to the decreased food intake. Most metabolites (>70%) cross species to humans, suggesting that the HPLC-based technique used identifies broadly conserved metabolites. We now propose to use our existing bio-informatics platform to reexamine our existing rat sera metabolomics data (>600 rats, --600,000 data-points) to identify biomarkers and metabolic profiles reflective of the aging process. This work extends our ongoing work into a new direction: a metabolome-based approach to aspects of aging. The work will be completed in the context of 4 focused Aims: Aim 1. To determine the extent to which previously identified biomarkers of DR are also biomarkers of aging. Aim 2. To determine the extent to metabolites in major metabolic pathways (e.g., purines, tyrosine metabolites, tryptophan metabolites, antioxidants, neurotransmitters) are also biomarkers of aging. Aim 3. To identify previously unstudied metabolites that are modulated by the aging process The markers studied in Aims 1-3 have complementary advantages for future studies: (a) likely correlation of biomarkers of aging and those of physiological deterioration captured by DR; (b) the broad literature on compounds in major pathways, and; (c) the potential to open new vistas with previously undefined markers. Aim 4. To use the biomarkers above to build metabolic profiles of the aging process Profiles will be examined/generated using megavariate approaches available in the laboratory (e.g., 1 and 2-D clustering, heat maps, self-organizing maps, principal components analysis, partial least squares, partial least squares projection to latent structures discriminant analysis, etc).